When editing images, there are two “generic” types of editing adjustments. Global adjustments, such as tone curves, levels, and saturation apply universally to the entire image. Local adjustments are typically thought of to be “brushing” type adjustments where the user manually “brushes” in adjustments to specific areas of the image that they are interested in. Global adjustments ignore differences between different local areas of an image and often result in an adjustment image that is either too dark in certain areas or too bright in certain areas.
Brush-type local adjustment often creates disconnection between brushed area and its surrounding areas. Global adjustment is more efficient but often leads to over exposure and under exposure. Global adjustment can also create areas that are too saturated (e.g., in skin tones) or not saturated enough (e.g., in colorful flowers or skies). In addition, applying brush-type local adjustment is manual, time consuming and tedious.
What is needed in the art are methods and systems that can balance the two type of approaches to create efficient and yet localized image editing.